Summary
Alberto Boldrini is a Principal Scientist in Computational Biophysics with a strong blend of physics, numerical computing and software engineering, bringing over a decade of experience in C++ and Python to molecular simulation and analysis. At Sibylla Biotech he develops enhanced-sampling MD methods, AI-augmented pocket detection and graph neural network predictors, and builds production-ready tooling for clustering and estimating simulation-derived quantities. His background in low-latency algorithmic trading and hands-on networking/cluster management gives him uncommon expertise in performance optimization and infrastructure for high-throughput simulations. Trained in physics and quantitative computational biology at Università di Trento, he combines rigorous theoretical foundations with pragmatic code optimizations to turn complex biophysical models into efficient, scalable software.
8 years of coding experience
Laurea Magistrale LM Quantitative and Computational Biology, Laurea Magistrale LM Quantitative and Computational Biology at Università di Trento